Surgery and transplantation – Guidelines on Parenteral Nutrition, Chapter 18

In surgery, indications for artificial nutrition comprise prevention and treatment of catabolism and malnutrition. Thus in general, food intake should not be interrupted postoperatively and the re-establishing of oral (e.g. after anastomosis of the colon and rectum, kidney transplantation) or enteral food intake (e.g. after an anastomosis in the upper gastrointestinal tract, liver transplantation) is recommended within 24 h post surgery. To avoid increased mortality an indication for an immediate postoperatively artificial nutrition (enteral or parenteral nutrition (PN)) also exists in patients with no signs of malnutrition, but who will not receive oral food intake for more than 7 days perioperatively or whose oral food intake does not meet their needs (e.g. less than 60–80%) for more than 14 days. In cases of absolute contraindication for enteral nutrition, there is an indication for total PN (TPN) such as in chronic intestinal obstruction with a relevant passage obstruction e.g. a peritoneal carcinoma. If energy and nutrient requirements cannot be met by oral and enteral intake alone, a combination of enteral and parenteral nutrition is indicated. Delaying surgery for a systematic nutrition therapy (enteral and parenteral) is only indicated if severe malnutrition is present. Preoperative nutrition therapy should preferably be conducted prior to hospital admission to lower the risk of nosocomial infections. The recommendations of early postoperative re-establishing oral feeding, generally apply also to paediatric patients. Standardised operative procedures should be established in order to guarantee an effective nutrition therapy

A genetic programming based fuzzy regression approach to modelling manufacturing processes

Fuzzy regression has demonstrated its ability to model manufacturing processes in which the processes have fuzziness and the number of experimental data sets for modelling them is limited. However, previous studies only yield fuzzy linear regression based process models in which variables or higher order terms are not addressed. In fact, it is widely recognised that behaviours of manufacturing processes do often carry interactions among variables or higher order terms. In this paper, a genetic programming based fuzzy regression GP-FR, is proposed for modelling manufacturing processes. The proposed method uses the general outcome of GP to construct models the structure of which is based on a tree representation, which could carry interaction and higher order terms. Then, a fuzzy linear regression algorithm is used to estimate the contributions and the fuzziness of each branch of the tree, so as to determine the fuzzy parameters of the genetic programming based fuzzy regression model.To evaluate the effectiveness of the proposed method for process modelling, it was applied to the modelling of a solder paste dispensing process. Results were compared with those based on statistical regression and fuzzy linear regression. It was found that the proposed method can achieve better goodness-of-fitness than the other two methods. Also the prediction accuracy of the model developed based on GP-FR is better than those based on the other two methods

Human resources issues and Australian Disaster Medical Assistance Teams: results of a national survey of team members

Background: Calls for disaster medical assistance teams (DMATs) are likely to continue in response to international disasters. As part of a national survey, this study was designed to evaluate Australian DMAT experience in relation to the human resources issues associated with deployment.\ud \ud Methods: Data was collected via an anonymous mailed survey distributed via State and Territory representatives on the Australian Health Protection Committee, who identified team members associated with Australian DMAT deployments from the 2004 South East Asian Tsunami disaster.\ud \ud Results: The response rate for this survey was 50% (59/118). Most personnel had deployed to the Asian Tsunami affected areas with DMAT members having significant clinical and international experience. While all except one respondent stated they received a full orientation prior to deployment, only 34% of respondents (20/59) felt their role was clearly defined pre deployment. Approximately 56% (33/59) felt their actual role matched their intended role and that their clinical background was well suited to their tasks. Most respondents were prepared to be available for deployment for 1 month (34%, 20/59). The most common period of notice needed to deploy was 6–12 hours for 29% (17/59) followed by 12–24 hours for 24% (14/59). The preferred period of overseas deployment was 14–21 days (46%, 27/59) followed by 1 month (25%, 15/59) and the optimum shift period was felt to be 12 hours by 66% (39/59). The majority felt that there was both adequate pay (71%, 42/59) and adequate indemnity (66%, 39/59). Almost half (49%, 29/59) stated it was better to work with people from the same hospital and, while most felt their deployment could be easily covered by staff from their workplace (56%, 33/59) and caused an inconvenience to their colleagues (51%, 30/59), it was less likely to interrupt service delivery in their workplace (10%, 6/59) or cause an inconvenience to patients (9%, 5/59). Deployment was felt to benefit the affected community by nearly all (95%, 56/59) while less (42%, 25/59) felt that there was a benefit for their own local community. Nearly all felt their role was recognised on return (93%, 55/59) and an identical number (93%, 55/59) enjoyed the experience. All stated they would volunteer again, with 88% strongly agreeing with this statement.\ud \ud Conclusions: This study of Australian DMAT members provides significant insights into a number of human resources issues and should help guide future deployments. The preferred 'on call' arrangements, notice to deploy, period of overseas deployment and shift length are all identified. This extended period of operations needs to be supported by planning and provision of rest cycles, food, temporary accommodation and rest areas for staff. The study also suggests that more emphasis should be placed on team selection and clarification of roles. While the majority felt that there was both adequate pay and adequate indemnity, further work clarifying this, based on national conditions of service should be, and are, being explored currently by the state based teams in Australia. Importantly, the deployment was viewed positively by team members who all stated they would volunteer again, which allows the development of an experienced cohort of team members

Accelerated search for biomolecular network models to interpret high-throughput experimental data

<p>Abstract</p> <p>Background</p> <p>The functions of human cells are carried out by biomolecular networks, which include proteins, genes, and regulatory sites within DNA that encode and control protein expression. Models of biomolecular network structure and dynamics can be inferred from high-throughput measurements of gene and protein expression. We build on our previously developed fuzzy logic method for bridging quantitative and qualitative biological data to address the challenges of noisy, low resolution high-throughput measurements, i.e., from gene expression microarrays. We employ an evolutionary search algorithm to accelerate the search for hypothetical fuzzy biomolecular network models consistent with a biological data set. We also develop a method to estimate the probability of a potential network model fitting a set of data by chance. The resulting metric provides an estimate of both model quality and dataset quality, identifying data that are too noisy to identify meaningful correlations between the measured variables.</p> <p>Results</p> <p>Optimal parameters for the evolutionary search were identified based on artificial data, and the algorithm showed scalable and consistent performance for as many as 150 variables. The method was tested on previously published human cell cycle gene expression microarray data sets. The evolutionary search method was found to converge to the results of exhaustive search. The randomized evolutionary search was able to converge on a set of similar best-fitting network models on different training data sets after 30 generations running 30 models per generation. Consistent results were found regardless of which of the published data sets were used to train or verify the quantitative predictions of the best-fitting models for cell cycle gene dynamics.</p> <p>Conclusion</p> <p>Our results demonstrate the capability of scalable evolutionary search for fuzzy network models to address the problem of inferring models based on complex, noisy biomolecular data sets. This approach yields multiple alternative models that are consistent with the data, yielding a constrained set of hypotheses that can be used to optimally design subsequent experiments.</p

Computational Models of Classical Conditioning guest editors’ introduction

In the present special issue, the performance of current computational models of classical conditioning was evaluated under three requirements: (1) Models were to be tested against a list of previously agreed-upon phenomena; (2) the parameters were fixed across simulations; and (3) the simulations used to test the models had to be made available. These requirements resulted in three major products: (a) a list of fundamental classical-conditioning results for which there is a consensus about their reliability; (b) the necessary information to evaluate each of the models on the basis of its ordinal successes in accounting for the experimental data; and (c) a repository of computational models ready to generate simulations. We believe that the contents of this issue represent the 2012 state of the art in computational modeling of classical conditioning and provide a way to find promising avenues for future model development

The effects of pulmonary rehabilitation in patients with non-cystic fibrosis bronchiectasis: protocol for a randomised controlled trial

BACKGROUND: Non-cystic fibrosis bronchiectasis is characterised by sputum production, exercise limitation and recurrent infections. Although pulmonary rehabilitation is advocated for this patient group, its effects are unclear. The aims of this study are to determine the short and long term effects of pulmonary rehabilitation on exercise capacity, cough, quality of life and the incidence of acute pulmonary exacerbations. METHODS/DESIGN: This randomised controlled trial aims to recruit 64 patients with bronchiectasis from three tertiary institutions. Participants will be randomly allocated to the intervention group (supervised, twice weekly exercise training with regular review of airway clearance therapy) or a control group (twice weekly telephone support). Measurements will be taken at baseline, immediately following the intervention and at six and 12 months following the intervention period by a blinded assessor. Exercise capacity will be measured using the incremental shuttle walk test and the six-minute walk test. Quality of life and health status will be measured using the Chronic Respiratory Questionnaire, Leicester Cough Questionnaire, Assessment of Quality of Life Questionnaire and the Hospital Anxiety and Depression Scale. The rate of hospitalisation will be captured as well as the incidence of acute pulmonary exacerbations using a daily symptom diary. DISCUSSION: Results from this study will help to determine the efficacy of supervised twice-weekly pulmonary rehabilitation upon exercise capacity and quality of life in patients with bronchiectasis and will contribute to clinical practice guidelines for physiotherapists in the management of this population. TRIAL REGISTRATION: This study protocol is registered with ClinicalTrials.gov (NCT00885521)

Control Growth Factor Release Using a Self-Assembled [polycation∶heparin] Complex

The importance of growth factors has been recognized for over five decades; however their utilization in medicine has yet to be fully realized. This is because free growth factors have short half-lives in plasma, making direct injection inefficient. Many growth factors are anchored and protected by sulfated glycosaminoglycans in the body. We set out to explore the use of heparin, a well-characterized sulfated glycosaminoglycan, for the controlled release of fibroblast growth factor-2 (FGF-2). Heparin binds a multitude of growth factors and maintains their bioactivity for an extended period of time. We used a biocompatible polycation to precipitate out the [heparin∶FGF-2] complex from neutral buffer to form a release matrix. We can control the release rate of FGF-2 from the resultant matrix by altering the molecular weight of the polycation. The FGF-2 released from the delivery complex maintained its bioactivity and initiated cellular responses that were at least as potent as fresh bolus FGF-2 and fresh heparin stabilized FGF-2. This new delivery platform is not limited to FGF-2 but applicable to the large family of heparin-binding growth factors

An approach for particle sinking velocity measurements in the 3–400 μm size range and considerations on the effect of temperature on sinking rates

The flux of organic particles below the mixed layer is one major pathway of carbon from the surface into the deep ocean. The magnitude of this export flux depends on two major processes—remineralization rates and sinking velocities. Here, we present an efficient method to measure sinking velocities of particles in the size range from approximately 3–400 μm by means of video microscopy (FlowCAM®). The method allows rapid measurement and automated analysis of mixed samples and was tested with polystyrene beads, different phytoplankton species, and sediment trap material. Sinking velocities of polystyrene beads were close to theoretical values calculated from Stokes’ Law. Sinking velocities of the investigated phytoplankton species were in reasonable agreement with published literature values and sinking velocities of material collected in sediment trap increased with particle size. Temperature had a strong effect on sinking velocities due to its influence on seawater viscosity and density. An increase in 9 °C led to a measured increase in sinking velocities of ~40 %. According to this temperature effect, an average temperature increase in 2 °C as projected for the sea surface by the end of this century could increase sinking velocities by about 6 % which might have feedbacks on carbon export into the deep ocean

RNAi Targeting of West Nile Virus in Mosquito Midguts Promotes Virus Diversification

West Nile virus (WNV) exists in nature as a genetically diverse population of competing genomes. This high genetic diversity and concomitant adaptive plasticity has facilitated the rapid adaptation of WNV to North American transmission cycles and contributed to its explosive spread throughout the New World. WNV is maintained in nature in a transmission cycle between mosquitoes and birds, with intrahost genetic diversity highest in mosquitoes. The mechanistic basis for this increase in genetic diversity in mosquitoes is poorly understood. To determine whether the high mutational diversity of WNV in mosquitoes is driven by RNA interference (RNAi), we characterized the RNAi response to WNV in the midguts of orally exposed Culex pipiens quinquefasciatus using high-throughput, massively parallel sequencing and estimated viral genetic diversity. Our data demonstrate that WNV infection in orally exposed vector mosquitoes induces the RNAi pathway and that regions of the WNV genome that are more intensely targeted by RNAi are more likely to contain point mutations compared to weakly targeted regions. These results suggest that, under natural conditions, positive selection of WNV within mosquitoes is stronger in regions highly targeted by the host RNAi response. Further, they provide a mechanistic basis for the relative importance of mosquitoes in driving WNV diversification

The identification of QTL controlling ergot sclerotia size in hexaploid wheat implicates a role for the Rht dwarfing alleles

The fungal pathogen Claviceps purpurea infects ovaries of a broad range of temperate grasses and cereals, including hexaploid wheat, causing a disease commonly known as ergot. Sclerotia produced in place of seed carry a cocktail of harmful alkaloid compounds that result in a range of symptoms in humans and animals, causing ergotism. Following a field assessment of C. purpurea infection in winter wheat, two varieties ‘Robigus’ and ‘Solstice’ were selected which consistently produced the largest differential effect on ergot sclerotia weights. They were crossed to produce a doubled haploid mapping population, and a marker map, consisting of 714 genetic loci and a total length of 2895 cM was produced. Four ergot reducing QTL were identified using both sclerotia weight and size as phenotypic parameters; QCp.niab.2A and QCp.niab.4B being detected in the wheat variety ‘Robigus’, and QCp.niab.6A and QCp.niab.4D in the variety ‘Solstice’. The ergot resistance QTL QCp.niab.4B and QCp.niab.4D peaks mapped to the same markers as the known reduced height (Rht) loci on chromosomes 4B and 4D, Rht-B1 and Rht-D1, respectively. In both cases, the reduction in sclerotia weight and size was associated with the semi-dwarfing alleles, Rht-B1b from ‘Robigus’ and Rht-D1b from ‘Solstice’. Two-dimensional, two-QTL scans identified significant additive interactions between QTL QCp.niab.4B and QCp.niab.4D, and between QCp.niab.2A and QCp.niab.4B when looking at sclerotia size, but not between QCp.niab.2A and QCp.niab.4D. The two plant height QTL, QPh.niab.4B and QPh.niab.4D, which mapped to the same locations as QCp.niab.4B and QCp.niab.4D, also displayed significant genetic interactions